Meet Tempo

What is Tempo?

Tempo is a hosted platform for building end-to-end machine learning applications using our proprietary automation technology.

Tempo automates the three steps in a machine learning endeavor

Prediction Engineering

Identify the specific problem to address your business need

Automated Feature Engineering

Intelligently extract the most important predictive signals

Machine Learning

Automatically learn rules from historical data that can be applied to new data

Prediction Engineering

Hone in on the business need

Translate a business need into historical training examples for ML algorithms to learn from.

Make ML Pervasive

Easily define new machine learning problems across your business.

Experiment for maximum impact

Reduce the time needed to iterate on different formulations of the same problem.

Forecast Future SpendingCreated with Sketch.JaromApril 16, 2018$0$33$113$50SamMarch 23, 2018JohnMar 12, 2018Feb 23, 2018CarlyCUTOFF TIMEFUTURE SPENDINGCUSTOMERExtract Training ExamplesTempo scans your historical data to find past customers to learn formYour Training ExamplesUsing the data from before the cutoff time, we can learn from these examplecustomer how to predict future spendingForecast windowThe future period of time to calculate total spending30 DaysLead timeIncreasing the lead gives you more time to act on the prediction7 DaysSpending in last monthTarget your customer who spent at least this much$300EXTRACTForecast Future Customer Spending

Deep Future SyntesisCreated with Sketch.Deep Feature Syntesis1.0MEAN(sessions.COUNT(events))Average number of events per session for a user7Max(sessions.SUM(total))0.5TREND(sessions.AvgTimeBetween(start_time))Rate of change of the average time between a user’s sessionsSelect PrimitivesRecommended FeaturesTRENDAVG. TIME BETWEENCOUNTMEANMENUSUMSUM

Leave no stone unturned

Customize to your data

Write custom primitives to extend our continually growing library.

Deep Future SyntesisCreated with Sketch.Deep Feature Syntesis1.0MEAN(sessions.COUNT(events))Average number of events per session for a user7Max(sessions.SUM(total))0.5TREND(sessions.AvgTimeBetween(start_time))Rate of change of the average time between a user’s sessionsSelect PrimitivesRecommended FeaturesTRENDAVG. TIME BETWEENCOUNTMEANMENUSUMSUM

Machine Learning

Find the best model

Automatically search numerous modeling pipelines to find the one with best performance

Validate the model

Test your model to ensure it will produce trustworthy predictions on future data.

Deploy with ease

Export modeling code or use Tempo’s hosted APIs to put machine learning to work for you

Model SearchCreated with Sketch.ProgressWhat would you like to de next?Evaluate against baseline• Configure ROI ParametersSelect modeling algorithm• Export deployment codeCalculate ROI• Request data scientist auditExport deployment code• View top features• Select Different ModelAccuracy90%30% better than baseline$190KFeatures24Your ModelVERIFIEDUsing the data from before the cutoff time, we can use these example customer to learn how to predict future spendingModel Search